Orbicon is a centralized place where you can find anything about your developer community. Orbit aggregates all sorts of different events coming from the community, while Memgraph enriches the data and provides advanced insights based on incremental graph algorithms.
Orbit provides the Love metric, which indicates how much a given community member loves your brand. In addition to data coming from Orbit, Memgraph scrapes social graph data from Github and Twitter. Based on these social networks, Memgraph constructs an entirely new membership graph. Memgraph then analyzes this membership graph by applying the following graph algorithms:
- PageRank: This algorithm tells us how important each member is.
- Community Detection: This algorithm reveals deeper insights about the network structure and possible sub-communities.
- The demo application - orbit.memgraph.com
- The Memgraph instance - bolt://orbit.memgraph.com:7687
To explore the data, please download Memgraph
Lab. The endpoint is orbit.memgraph.com and
the port is 7687.
The first thing to do in the root directory is to create a Python virtual environment:
python3 -m venv .venv
source .venv/bin/activate
After that, install all the dependencies with Poetry:
cd backend
poetry install
Finally, start the backend service with:
python3 main.py
Position yourself in the frontend directory, install the dependencies with npm and run using the following commands:
cd frontend
npm install
npm run serve
Memgraph makes creating real-time streaming graph applications accessible to every developer. Spin up an instance, consume data directly from Kafka, and build on top of everything from super-fast graph queries to PageRank and Community Detection.
Thanks goes to these wonderful people (emoji key):
 Josip Mrden |
 Marko Budiselic |
 Antonio Filipovic |
This project follows the all-contributors specification. Contributions of any kind welcome!